Joint Extraction Model of Entities and Events

DOI

10.2991/icmeit-19.2019.117How to use a DOI?

Keywords

entity recognition, event extraction, the joint model.

Abstract

Joint extraction of entities and events is an important task in information extraction. In order to obtain entities and events in the text simultaneously, in this paper we firstly propose a novel tagging scheme that can transform the joint extraction task to a tagging problem. Then, based on our tagging scheme, we use different end-to-end models to extract entities and events directly and we also propose an improved objective function with different parameters to express the importance of different labels. We conduct experiments on a financial dataset and the results show that our methods are better than other existing models.

Copyright

© 2019, the Authors. Published by Atlantis Press.

Open Access

This is an open access article distributed under the CC BY-NC license (http://creativecommons.org/licenses/by-nc/4.0/).

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TY  - CONF
AU  - Can Tian
AU  - Yawei Zhao
AU  - Liang Ren
PY  - 2019/04
DA  - 2019/04
TI  - Joint Extraction Model of Entities and Events
BT  - Proceedings of the 3rd International Conference on Mechatronics Engineering and Information Technology (ICMEIT 2019)
PB  - Atlantis Press
SP  - 736
EP  - 743
SN  - 2352-538X
UR  - https://doi.org/10.2991/icmeit-19.2019.117
DO  - 10.2991/icmeit-19.2019.117
ID  - Tian2019/04
ER  -